Total 50,502 skills, AI & Machine Learning has 8478 skills
Showing 12 of 8478 skills
Generate UGC-style (User Generated Content) lifestyle photos of a person wearing or using your product — authentic, relatable, social-media-native imagery.
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm. Use this skill whenever the user is building any system that picks "the top K items for a (user, context)" — social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.
Agente que simula Bill Gates — cofundador da Microsoft, arquiteto da industria de software comercial, estrategista tecnologico global, investidor sistemico e filantropo baseado em dados.
Self-referential development loop with ultrawork mode - continues until verified task completion
Internal support skill for actionbook MCP selectors used by Rust documentation research workflows. Use only when another rust-skills workflow explicitly requests actionbook-backed selectors.
agent-team: Read messages for one recipient agent.
agent-team: Show one workflow run and grouped task status counts.
Turn video moments into AI-generated hand-drawn storyboards with Gemini-powered frame analysis and social media content generation
Produce a token-bounded context pack from the Obsidian wiki — a compact, structured slice of the most relevant pages for a topic or recent activity, designed for downstream consumption by another agent or skill. Use when the user says "/wiki-context-pack", "make a context pack", "give me a context slice for X", "pack the wiki for my agent", or "bounded context for Y". Different from wiki-query (which answers a question) — this produces reusable input material for a downstream task.
This skill should be used when the user asks to "test the triage skill", "run triage tests", "validate antithesis triage", "test:triage", or "smoke test triage". Orchestrates end-to-end testing of the antithesis-triage skill by running real triage operations via sub-agents and reviewing the results for bugs, skill compliance issues, and papercuts.
Scan an experiment repo and generate a complete paper outline (H1/H2/H3) with user approval checkpoints at each level, then generate body text with evidence annotations, citations, and bilingual output. Python ML repos. 扫描实验仓库，逐级生成论文大纲（H1/H2/H3），每级用户确认后推进， 然后生成带证据标注、引用和双语输出的正文文本。